What are some references that describe known filters (or kernels) and how we can create new ones?
I'd suggest you better understand edge detectors such as Robert or Sobel operators first to understand better how convolution operation on images extract features by constant value kernels.  

Would personally recommend Gonzales and Woods for this,  as it gives a pure mathematical explanation to how and why these features are extracted.

Essentially the convolution kernels used in CNN's are ones with a learned set of values for the kernel. 

For a better understanding of learned convolution kernels and, quite frankly, any idea under deep learning would easily recommend Deep Learning by Goodfellow et al